As the use of mobile devices becomes more ubiquitous, advertisers and brand owners strive to leverage the physical or geographical location of the mobile device and the intent of a respective mobile device user in order to drive highly targeted advertising campaigns. Some legacy systems deploy GPS technology to provide geographically relevant data. For example, a search for restaurants using the map application on a mobile phone will use GPS to determine a list of restaurants near the current device location. To establish a more precise location, other legacy systems deploy one or more small wireless transmitters or “location beacons” that communicate with nearby devices using short-range wireless technology (e.g., Bluetooth low energy or BLE technology). In such cases, the term nearby refers to the theoretical range of BLE beacons (e.g., about 100 meters). For example, Major League Baseball has deployed beacons to at least 20 baseball stadiums for various purposes. Over 25,000 other beacons have also been deployed to various other sites (e.g., retail stores) for various other purposes.
When a receiver (e.g., in a mobile device) is in range of a beacon and establishes a communication link, the beacon provides signals (e.g., packets of data) that comprise a location beacon identification value that can be detected by the receiver, and from which signals or packets the receiver can determine the identity of the beacon or beacons it is near. The beacon identification value can be formed of an identifier that is specific to each beacon (e.g., unique to each beacon from among a larger set of beacons). The distance from each beacon can be determined, at least in part from the received signal strength. For example, a retail store can use a BLE beacon to detect when a device enters the store in order to deliver product discount coupons or some other push notification to the device using an application running on the device.
Certain uses of, or combinations of, the aforementioned legacy systems and techniques can serve to determine the geographical location of a given device. However, advertisers may also want to know more about the device user's activity and intentions at a particular location. Advertisers may additionally desire user device data from other locations and even other devices a user may have (e.g., a laptop, a tablet device, etc.). Further, advertisers may want to leverage the vast amount of online user demographics and other user-specific data when determining messaging to deliver to a user's mobile device. As a specific example, advertisers and/or brand owners might want to deploy beacons at certain product booths at a tradeshow. In such cases, the occurrence of a visit such as a walk-by or momentary pause by a visitor, including anonymous visitors that are nearby a booth having a beacon, can be registered. The visitor can then be the recipient of various communications (e.g., marketing communications via campaigns using Twitter, Google, etc.) and/or communications to drive a call to action (e.g., go to a website, provide contact information, download a whitepaper, etc.). In another example, advertisers and/or brand owners might want to place beacons in proximity of certain products in a store (e.g., white wine and red wine) to capture the appearance of users near those products. The advertisers and/or brand owners might want to push notifications (e.g., coupons, new product information, etc.) and alerts (e.g., soon-expiring promotions, availability of cross-promotions, etc.) based on their current location, previous visits, time at each location, offline activity (e.g., online wine buying), and other information.
Unfortunately, performing spatial and temporal analysis and/or applying spatial and/or temporal rules over a user and his/her mobile device and their location and movement does not scale as the number of users gets large. Legacy attempts are limited in their use and application of technology in that they fail to scale as users, devices and venues are added, and legacy attempts place unnecessary burdens on centralized computing infrastructures.
None of the aforementioned legacy approaches achieve the capabilities as herein-disclosed. Therefore, there is a need for improvements.